Evidence for the adsorption of molecules at special sites located at copper/zinc oxide interfaces. Part 3. -- Fourier-transform infrared study of methyl formate adsorption on reduced and oxidised Cu/ZnO/SiO2 catalysts

FTIR spectra are reported of methyl formate adsorbed at 295 K on ZnO/SiO2, reduced Cu/ZnO/SiO2 and on Cu/ZnO/SiO2 which had been preoxidised by exposure to nitrous oxide. Methyl formate on ZnO/SiO2 gave adsorbed zinc formate species and strongly physisorbed molecular methanol on silica. The comparable reaction of methyl formate with reduced Cu/ZnO/SiO2 catalyst produced bridging formate species on copper and a diminished quantity of zinc formate relative to that formed on ZnO/SiO2 catalyst. This effect is explained in terms of site blockage on the ZnO surface by small copper clusters. Addition of methyl formate to a reoxidised Cu/ZnO/SiO2 catalyst produced a considerably greater amount of formate species on zinc oxide and methoxy groups on copper were detected. The increase in concentration of zinc formate species was rationalised in terms of rearrangement of unidentate copper formate species to become bonded to copper and zinc oxide sites located at the interface between these two components.

NTCIR-10 crosslink-2 task : a link mining strategy

At NTCIR-10 we participated in the cross-lingual link discovery (CrossLink-2) task. In this paper we describe our systems for discovering cross-lingual links between the Chinese, Japanese, and Korean (CJK) Wikipedia and the English Wikipedia. The evaluation results show that our implementation of the cross-lingual linking method achieved promising results.

A fourier-transform infrared study of CO2 and CO2/H2 interactions with caesium-doped copper catalysts

FTIR spectra are reported of CO2 and COi/Hi on a silica-supported caesium-doped copper catalyst. Adsorption of COj on a "caesium"/silica surface resulted in the formation of COj and complexed CO species. Exposure of CO2 to' a caesium-doped reduced copper catalyst produced not only these species but also two forms of adsorbed carboxylate giving bands at 1550, 1510, 1365 and 1345 cm"1. Reaction of carboxylate species with hydrogen at 388 K gave formate species on copper and caesium oxide in addition to methoxy groups associated with caesium oxide. Methoxy species were not detected on undoped copper catalyst suggesting that caesium may be a promoter for the methanol synthesis reaction. Methanol decomposition on a caesium-doped copper catalyst produced a small number of formate species on copper and caesium oxide. Methoxy groups on caesium oxide decomposed to CO and U.2, and subsequent reaction between CO and adsorbed oxygen resulted in carboxylate formation. Methoxy species located at interfacial sites appeared to exhibit unusual adsorption properties.

A data mining driven risk profiling method for road asset management

Road surface skid resistance has been shown to have a strong relationship to road crash risk, however, applying the current method of using investigatory levels to identify crash prone roads is problematic as they may fail in identifying risky roads outside of the norm. The proposed method analyses a complex and formerly impenetrable volume of data from roads and crashes using data mining. This method rapidly identifies roads with elevated crash-rate, potentially due to skid resistance deficit, for investigation. A hypothetical skid resistance/crash risk curve is developed for each road segment, driven by the model deployed in a novel regression tree extrapolation method. The method potentially solves the problem of missing skid resistance values which occurs during network-wide crash analysis, and allows risk assessment of the major proportion of roads without skid resistance values.

A data mining framework for relevance feature discovery

This thesis is a study for automatic discovery of text features for describing user information needs. It presents an innovative data-mining approach that discovers useful knowledge from both relevance and non-relevance feedback information. The proposed approach can largely reduce noises in discovered patterns and significantly improve the performance of text mining systems. This study provides a promising method for the study of Data Mining and Web Intelligence.

Mining temporal and spatial travel regularities for transit planning

Smart Card data from Automated Fare Collection system has been considered as a promising source of information for transit planning. However, literature has been limited to mining travel patterns from transit users and suggesting the potential of using this information. This paper proposes a method for mining spatial regular origins-destinations and temporal habitual travelling time from transit users. These travel regularity are discussed as being useful for transit planning. After reconstructing the travel itineraries, three levels of Density-Based Spatial Clustering of Application with Noise (DBSCAN) have been utilised to retrieve travel regularity of each of each frequent transit users. Analyses of passenger classifications and personal travel time variability estimation are performed as the examples of using travel regularity in transit planning. The methodology introduced in this paper is of interest for transit authorities in planning and managements

Personalized ontology learning for enhancing text mining effectiveness

Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

A people-to-people matching system using graph mining techniques

A people-to-people matching system (or a match-making system) refers to a system in which users join with the objective of meeting other users with the common need. Some real-world examples of these systems are employer-employee (in job search networks), mentor-student (in university social networks), consume-to-consumer (in marketplaces) and male-female (in an online dating network). The network underlying in these systems consists of two groups of users, and the relationships between users need to be captured for developing an efficient match-making system. Most of the existing studies utilize information either about each of the users in isolation or their interaction separately, and develop recommender systems using the one form of information only. It is imperative to understand the linkages among the users in the network and use them in developing a match-making system. This study utilizes several social network analysis methods such as graph theory, small world phenomenon, centrality analysis, density analysis to gain insight into the entities and their relationships present in this network. This paper also proposes a new type of graph called “attributed bipartite graph”. By using these analyses and the proposed type of graph, an efficient hybrid recommender system is developed which generates recommendation for new users as well as shows improvement in accuracy over the baseline methods.

Yttrium barium copper oxide thin films on yttria-stabilized zirconia: growth and properties

Y Ba Cu oxide thin films were grown epitaxially on single cryst. yttria-stabilized zirconia substrates by laser deposition. [on SciFinder(R)]

Very thin yttrium barium copper oxide films made by coevaporation

Superconducting YBa2Cu3O7 thin films with various thicknesses from 100 Å to 5000 Å were deposited on (100) SrTiO3 substrates with std. BaF2 coevaporation process. The films had crit. temps. of up to 93 K. The best crit. currents were 1 × 106 A/cm2 at 77 K and 3 × 107 A/cm2 at 4.2 K. The crit. current was generally higher for thinner films. Two different etching methods were used to pattern the films for jc measurements: Ar ion etching and EDTA wet etching. The wet etching was found to work well for thicker films (>1000 Å). For the thinner films, the ion etching process was preferred because of the reduced film surface degrdn. [on SciFinder(R)]

A study of localised galvanic replacement of copper and silver films with gold using scanning electrochemical microscopy

Galvanic replacement represents a highly significant process for the fabrication of bimetallic materials, but to date its application has been limited to either modification of large area metal surfaces or nanoparticles in solution. Here, the localised surface modification of copper and silver substrates with gold through the galvanic replacement process is reported. This was achieved by generation of a localised flux of AuCl4− ions from a gold ultramicroelectrode tip which interacts with the unbiased substrate of interest. The extent of modification with gold can be controlled through the tip–substrate distance and electrolysis time.

Large amplitude Fourier transformed AC voltammetric investigation of the active state electrochemistry of a copper/aqueous base interface and implications for electrocatalysis

The higher harmonic components available from large-amplitude Fourier-transformed alternating current (FT-ac) voltammetry enable the surface active state of a copper electrode in basic media to be probed in much more detail than possible with previously used dc methods. In particular, the absence of capacitance background current allows low-level Faradaic current contributions of fast electron-transfer processes to be detected; these are usually completely undetectable under conditions of dc cyclic voltammetry. Under high harmonic FT-ac voltammetric conditions, copper electrodes exhibit well-defined and reversible premonolayer oxidation responses at potentials within the double layer region in basic 1.0 M NaOH media. This process is attributed to oxidation of copper adatoms (Cu*) of low bulk metal lattice coordination numbers to surface-bonded, reactive hydrated oxide species. Of further interest is the observation that cathodic polarization in 1.0 M NaOH significantly enhances the current detected in each of the fundamental to sixth FT-ac harmonic components in the Cu*/Cu hydrous oxide electron-transfer process which enables the underlying electron transfer processes in the higher harmonics to be studied under conditions where the dc capacitance response is suppressed; the results support the incipient hydrous oxide adatom mediator (IHOAM) model of electrocatalysis. The underlying quasi-reversible interfacial Cu*/Cu hydrous oxide process present under these conditions is shown to mediate the reduction of nitrate at a copper electrode, while the mediator for the hydrazine oxidation reaction appears to involve a different mediator or active state redox couple. Use of FT-ac voltammetry offers prospects for new insights into the nature of active sites and electrocatalysis at the electrode/solution interface of Group 11 metals in aqueous media.

Monitoring cuprous ion transport by scanning electrochemical microscopy during the course of copper electrodeposition

Scanning electrochemical microscopy (SECM), in the substrate generation–tip collection (SG-TC) mode, has been used to detect the cuprous ion intermediate formed during the course of electrodeposition of Cu metal from aqueous solution. Addition of chloride is confirmed to strongly stabilize the ion in aqueous solution and enhance the rate of Cu electrodeposition. This SECM method in the SG-TC mode offers an alternative to the rotating ring disk electrode (RRDE) technique for in situ studies on the effect of plating bath additives in metal electrodeposition. An attractive feature of the SECM relative to the RRDE method is that it allows qualitative aspects of the electrodeposition process to be studied in close proximity to the substrate in a simple and direct fashion using an inexpensive probe, and without the need for forced convection.

Electrochemical formation of porous copper 7, 7, 8, 8-tetracyanoquinodimethane and copper 2, 3, 5, 6-tetrafluoro-7, 7, 8, 8-tetracyanoquinodimethane honeycomb surfaces with superhydrophobic properties

The electrochemical formation of highly porous CuTCNQ (TCNQ = 7,7,8,8-tetracyanoquinodimethane) and CuTCNQF4 (TCNQF4 = 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane) materials was undertaken via the spontaneous redox reaction between a porous copper template, created using a hydrogen bubbling template technique, and an acetonitrile solution containing TCNQ or TCNQF4. It was found that activation of the surface via vigorous hydrogen evolution that occurs during porous copper deposition and TCNQ mass transport being hindered through the porous network of the copper template influenced the growth of CuTCNQ and CuTCNQF4. This approach resulted in the fabrication of a honeycomb layered type structure where the internal walls consist of very fine crystalline needles or spikes. This combination of microscopic and nanoscopic roughness was found to be extremely beneficial for anti-wetting properties where superhydrophobic materials with contact angles as high as 177° were created. Given that CuTCNQ and CuTCNQF4 have shown potential as molecular based electronic materials in the area of switching and field emission, the creation of a surface that is moisture resistant may be of applied interest.

Aqueous phase synthesis of copper nanoparticles : a link between heavy metal resistance and nanoparticle synthesis ability in bacterial systems

We demonstrate aqueous phase biosynthesis of phase-pure metallic copper nanoparticles (CuNPs) using a silver resistant bacterium Morganella morganii. This is particularly important considering that there has been no report that demonstrates biosynthesis and stabilization of pure copper nanoparticles in the aqueous phase. Electrochemical analysis of bacterial cells exposed to Cu2+ ions provides new insights into the mechanistic aspect of Cu2+ ion reduction within the bacterial cell and indicates a strong link between the silver and copper resistance machinery of bacteria in the context of metal ion reduction. The outcomes of this study take us a step closer towards designing rational strategies for biosynthesis of different metal nanoparticles using microorganisms.